AIMC Topic: Chromatin

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Chromatin accessibility prediction via a hybrid deep convolutional neural network.

Bioinformatics (Oxford, England)
MOTIVATION: A majority of known genetic variants associated with human-inherited diseases lie in non-coding regions that lack adequate interpretation, making it indispensable to systematically discover functional sites at the whole genome level and p...

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding.

Bioinformatics (Oxford, England)
MOTIVATION: Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing...

HIPred: an integrative approach to predicting haploinsufficient genes.

Bioinformatics (Oxford, England)
MOTIVATION: A major cause of autosomal dominant disease is haploinsufficiency, whereby a single copy of a gene is not sufficient to maintain the normal function of the gene. A large proportion of existing methods for predicting haploinsufficiency inc...

LncRNA ontology: inferring lncRNA functions based on chromatin states and expression patterns.

Oncotarget
Accumulating evidences suggest that long non-coding RNAs (lncRNAs) perform important functions. Genome-wide chromatin-states area rich source of information about cellular state, yielding insights beyond what is typically obtained by transcriptome pr...